Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/florianbruniaux/claude-code-plugins/plan-startgit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/florianbruniaux/claude-code-plugins/plan-start)<a href="https://agentmods.dev/commands/florianbruniaux/claude-code-plugins/plan-start"><img src="https://agentmods.dev/badge/commands/florianbruniaux/claude-code-plugins/plan-start.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00039 | $0.01615 |
| Opus 5 | $0.00019 | $0.00807 |
| Sonnet 5 | $0.00008 | $0.00323 |
| Haiku 4.5 | $0.00004 | $0.00161 |
Grade A, and why
plan-start scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Start — 5-Phase Planning
Analyze the request and produce a complete implementation plan through structured phases. No code is written. Every significant decision is recorded. Run /clear after this command before running /plan-validate.
Phase 1: PRD & Design Analysis
Step 1.1 — PRD Analysis
Skip if no PRD exists (refactor, infra change, bug fix).
Read all PRD files and docs/INFORMATION_ARCHITECTURE.md if present. Scan the codebase to understand current implementation status.
Surface findings in 3 buckets:
Missing requirements — acceptance criteria that are absent or incomplete Ambiguous requirements — items with multiple valid interpretations Compliance concerns — security, data privacy, API contract implications
For each finding: present options with concrete pros/cons. Discuss with user. Record every decision in the plan file under a ## Decisions section before moving on. Do not proceed past unresolved ambiguities.
Step 1.2 — Design Analysis
Skip if no UI changes are in scope.
Read: DESIGN_SYSTEM.md, existing UX ADRs, CLAUDE.md UX rules.
Produce specs for:
- Screen inventory: new/modified screens, route placement, component reuse audit
- State catalog: empty, loading, populated, error, and partial states for every interactive element
- Interaction specs: user flows (happy path + alternates), focus/keyboard behavior
- Animation specs: map each interaction to existing keyframes or specify new ones, include
prefers-reduced-motionfallbacks - Responsive behavior: breakpoints, web/mobile divergence decisions
- Accessibility: WAI-ARIA pattern selection, live regions, error visibility
Create Design ADRs for significant UX decisions (choice of interaction pattern, new animation convention, platform divergence). Record minor layout choices directly in the plan file.
Phase 2: Technical Analysis
Spawn 1-2 Explore agents for targeted codebase research. Run them in the background via Task tool.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 181 lines · 39 tokens per session scan A d44183a5018c
plan-start is a command published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 1,615 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
Other commands, from other repositories
aso
App Store Optimization command. iOS app listing analysis via the iTunes API, keyword optimization, and competitor comparison.
content-generate
Social media content generation command. Produces ready-to-use posts, captions, visual briefs, and hashtags for the given platform and type.
api-doc
API documentation generation. Scans route definitions and produces structured API docs.
audit
Quality audit command. Runs a systematic audit over code, structure, or process.
brief
Project briefing command. Turns raw project ideas into structured, actionable briefs.
changelog
Automatic changelog generation. Produces a structured changelog from commit history.